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Textbook in PDF format

Our work is intended to be a reference book for researchers and practitioners interested in gaining in-depth understanding of scatter search with the goal of expanding this methodology or applying it to solving difficult practical problems. The book could also be used to complement other materials in a graduate seminar on metaheuristic optimization. We believe that scatter search has great potential due to its flexibility and proven effectiveness. The scatter search framework can be adapted to tackle optimization problems in a variety of settings and we have tried to demonstrate this throughout the book. For example, we show adaptations that deal with several solutions representations, including continuous and binary variables as well as permutation vectors. We also address unconstrained and constrained problems to illustrate the malleability of the method.
To make the book accessible to a large audience, we begin with three tutorial chapters. Although there is some intentional repetition across tutorials, we recommend reading all three chapters before moving to the advanced topics. The tutorials introduce elements of scatter search in a succinct and illustrative way. This introduction is essential for the novice and might be helpfully reinforcing for the seasoned metaheuristic researcher and practitioner.
Tutorial: Unconstrained Nonlinear Optimization
Tutorial: 0-1 Knapsack Problems
Tutorial: Linear Ordering Problems. Advanced Scatter Search Designs
Use of Memory in Scatter Search
Connections with Other Population-Based Approaches
Scatter Search Applications
Commercial Scatter Search Implementation
Experiences and Future Directions